Journal Description
Modelling
Modelling
is an international, peer-reviewed, open access journal on theory and applications of modelling and simulation in engineering science, published quarterly online by MDPI.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within ESCI (Web of Science), Scopus, EBSCO, and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 15.8 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Journal Rank: CiteScore - Q1 (Mathematics (miscellaneous))
- Recognition of Reviewers: APC discount vouchers, optional signed peer review and reviewer names are published annually in the journal.
Impact Factor:
1.3 (2023);
5-Year Impact Factor:
1.4 (2023)
Latest Articles
Correctness Verification of Mutual Exclusion Algorithms by Model Checking
Modelling 2024, 5(3), 694-719; https://doi.org/10.3390/modelling5030037 (registering DOI) - 28 Jun 2024
Abstract
Mutual exclusion algorithms are at the heart of concurrent/parallel and distributed systems. It is well known that such algorithms are very difficult to analyze, and in the literature, different conjectures about starvation freedom and the number of by-passes (also called the overtaking factor)
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Mutual exclusion algorithms are at the heart of concurrent/parallel and distributed systems. It is well known that such algorithms are very difficult to analyze, and in the literature, different conjectures about starvation freedom and the number of by-passes (also called the overtaking factor) exist. The overtaking factor affects the (hopefully) bounded waiting time that a process competing for entering the critical section has to suffer before accessing the shared resource, have been formulated for specific algorithms. This paper proposes a novel modeling approach based on Timed Automata and the Uppaal toolset, which proves effective for studying all the properties of a mutual exclusion algorithm for N≥2 processes, by exhaustive model checking. Although the approach, as already confirmed by similar experiments reported in the literature, is not scalable due to state explosion problems and can be practically applied until N≤5, it is of great value for revealing the true properties of analyzed algorithms. For dimensions N>5, the Statistical Model Checker of Uppaal can be used, which, although based on simulations, can confirm properties by estimations and probabilities. This paper describes the proposed modeling and verification method and applies it to several mutual exclusion algorithms, thus retrieving known properties but also showing new results about properties often studied by informal reasoning.
Full article
Open AccessArticle
Multi-Criteria Response Surface Optimization of Centrifugal Pump Performance Using CFD for Wastewater Application
by
Edwin Pagayona and Jaime Honra
Modelling 2024, 5(3), 673-693; https://doi.org/10.3390/modelling5030036 - 27 Jun 2024
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The effective transport of high-viscosity fluids in wastewater treatment systems is heavily contingent upon the operational efficiency of centrifugal pumps. However, challenges arise in operating these pumps under such conditions due to the detrimental impact of viscosity. This study is focused on enhancing
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The effective transport of high-viscosity fluids in wastewater treatment systems is heavily contingent upon the operational efficiency of centrifugal pumps. However, challenges arise in operating these pumps under such conditions due to the detrimental impact of viscosity. This study is focused on enhancing the performance of centrifugal pumps by examining the influence of design and impeller configuration. By employing CFD analysis in ANSYS, this study examines the effects of varying inlet and outlet impeller diameters as well as different numbers of impeller blades on pump performance. The investigation entails three core stages: pre-processing, encompassing the creation of geometry, meshing, and study configuration; processing, which involves defining physics settings, selecting the solver type, and specifying boundary conditions; and post-processing, dedicated to the interpretation of results derived from model creation and solution. Leveraging Genetic Aggregation for response surface modelling facilitates the pinpointing of effective design configurations rooted in specific pump performance goals, thereby resulting in noteworthy performance enhancements. Notably, an optimal pump design featuring a 5-blade impeller with inlet and outlet diameters of 55.92 mm and 207.78 mm, respectively, yielded significant improvements of 26.51% in head, 2.53% in static efficiency, and 62.30% in incipient net positive suction head (NPSHi).
Full article
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Open AccessArticle
Impact of Volute Throat Area and Gap Width on the Hydraulic Performance of Low-Specific-Speed Centrifugal Pump
by
Muhammad Fasahat Khan, Tim Gjernes, Nicholas Guenther and Jean-Pierre Hickey
Modelling 2024, 5(3), 659-672; https://doi.org/10.3390/modelling5030035 - 26 Jun 2024
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This paper investigates the influence of the volute geometry on the hydraulic performance of a low-specific-speed centrifugal pump using numerical simulations. The performance characteristics for the pump with the volute geometry designed using the constant velocity method show a significant discrepancy between the
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This paper investigates the influence of the volute geometry on the hydraulic performance of a low-specific-speed centrifugal pump using numerical simulations. The performance characteristics for the pump with the volute geometry designed using the constant velocity method show a significant discrepancy between the design point and the best efficiency point (BEP). This design methodology also results in a relatively flat head–capacity curve. These are both undesirable characteristics which can be mitigated by a reduction in the volute throat area. This design methodology also leads to a reduction in the power consumption and an increase in efficiency, especially at underload and design flow conditions. These impacts of the volute throat area on performance characteristics are investigated in terms of the change in internal flow characteristics due to the reduction in the volute throat area. Another aspect of the study is the impact of the width of the volute gap on performance characteristics. A reduction in the gap width results in a nearly vertical shift of the head–capacity curve, so that head delivered is higher across all the flow rates as the gap width is reduced. This is also accompanied by a slight improvement in efficiency under design flow and overload conditions. Numerical simulations are used to relate the change in performance characteristics with internal flow characteristics.
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Open AccessArticle
Modeling and Optimization of Concrete Mixtures Using Machine Learning Estimators and Genetic Algorithms
by
Ana I. Oviedo, Jorge M. Londoño, John F. Vargas, Carolina Zuluaga and Ana Gómez
Modelling 2024, 5(3), 642-658; https://doi.org/10.3390/modelling5030034 - 24 Jun 2024
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This study presents a methodology to optimize concrete mixtures by integrating machine learning (ML) and genetic algorithms. ML models are used to predict compressive strength, while genetic algorithms optimize the mixture cost under quality constraints. Using a dataset of over 19,000 samples from
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This study presents a methodology to optimize concrete mixtures by integrating machine learning (ML) and genetic algorithms. ML models are used to predict compressive strength, while genetic algorithms optimize the mixture cost under quality constraints. Using a dataset of over 19,000 samples from a local ready-mix concrete producer, various predictive ML models were trained and evaluated regarding cost-effective solutions. The results show that the optimized mixtures meet the desired compressive strength range and are cost-efficient, thus having of the solutions yielding a cost below of the test cases. CatBoost emerged as the best ML technique, thereby achieving a mean absolute error (MAE) below 5 MPa. This combined approach enhances quality, reduces costs, and improves production efficiency in concrete manufacturing.
Full article
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Open AccessArticle
Micromechanical Estimates Compared to FE-Based Methods for Modelling the Behaviour of Micro-Cracked Viscoelastic Materials
by
Sarah Abou Chakra, Benoît Bary, Eric Lemarchand, Christophe Bourcier, Sylvie Granet and Jean Talandier
Modelling 2024, 5(2), 625-641; https://doi.org/10.3390/modelling5020033 - 20 Jun 2024
Abstract
The purpose of this study is to investigate the effective behaviour of a micro-cracked material whose matrix bulk and shear moduli are ruled by a linear viscoelastic Burgers model. The analysis includes a detailed study of randomly oriented and distributed cracks displaying an
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The purpose of this study is to investigate the effective behaviour of a micro-cracked material whose matrix bulk and shear moduli are ruled by a linear viscoelastic Burgers model. The analysis includes a detailed study of randomly oriented and distributed cracks displaying an overall isotropic behaviour, as well as aligned cracks resulting in a transversely isotropic medium. Effective material properties are approximated with the assumption that the homogenized equivalent medium exhibits the characteristics of a Burgers model, leading to the identification of short-term and long-term homogenized modules in the Laplace–Carson space through simplified formulations. The crucial advantage of this analytical technique consists in avoiding calculations of the inverse Laplace–Carson transform. The micromechanical estimates are validated through comparisons with FE numerical simulations on 3D microstructures generated with zero-thickness void cracks of disc shape. Intersections between randomly oriented cracks are accounted for, thereby highlighting a potential percolation phenomenon. The effects of micro-cracks on the material’s behaviour are then studied with the aim of providing high-performance creep models for macrostructure calculations at a moderate computation cost through the application of analytical homogenization techniques.
Full article
(This article belongs to the Special Issue Feature Papers of Computational Modelling and Simulation for Fatigue and Fracture of Engineering Materials and Structures)
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Open AccessArticle
Mixing Enhancement Study in Axisymmetric Trapped-Vortex Combustor for Propane, Ammonia and Hydrogen
by
Heval Serhat Uluk, Sam M. Dakka and Kuldeep Singh
Modelling 2024, 5(2), 600-624; https://doi.org/10.3390/modelling5020032 - 7 Jun 2024
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The trapped-vortex combustor (TVC) is an alternative combustor design to conventional aeroengine combustors. The separate fuel and air injection of this combustor and its compact design make it a perfect candidate for conventional fuel usage. Moreover, the performance of a trapped-vortex combustor with
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The trapped-vortex combustor (TVC) is an alternative combustor design to conventional aeroengine combustors. The separate fuel and air injection of this combustor and its compact design make it a perfect candidate for conventional fuel usage. Moreover, the performance of a trapped-vortex combustor with alternative fuels such as ammonia and hydrogen in the actual operating conditions of an aeroengine is not well understood. The present paper focused on the performance evaluation of TVCs with the futuristic fuels ammonia and hydrogen including under the realistic operating conditions of a combustor. The investigated fuels were injected into a cavity with 0-,15-, 30- and 45-degree transverse-angled air injectors to evaluate the mixing enhancement of the air and fuel under idle and low-power conditions. The mixing behavior of hydrogen showed a significant difference from the conventional fuel, i.e., propane. It was also noticed that the transverse injection of the air helped to improve the mixing efficiency as compared to the normal injection configuration. Mixing efficiency was higher for the 30- and 45-degree transverse-angled air injectors compared to the 0- and 15-degree transverse-angled air injectors.
Full article
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Open AccessArticle
Estimation Approach for a Linear Quantile-Regression Model with Long-Memory Stationary GARMA Errors
by
Oumaima Essefiani, Rachid El Halimi and Said Hamdoune
Modelling 2024, 5(2), 585-599; https://doi.org/10.3390/modelling5020031 - 4 Jun 2024
Abstract
The aim of this paper is to assess the significant impact of using quantile analysis in multiple fields of scientific research . Here, we focus on estimating conditional quantile functions when the errors follow a GARMA (Generalized Auto-Regressive Moving Average) model. Our key
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The aim of this paper is to assess the significant impact of using quantile analysis in multiple fields of scientific research . Here, we focus on estimating conditional quantile functions when the errors follow a GARMA (Generalized Auto-Regressive Moving Average) model. Our key theoretical contribution involves identifying the Quantile-Regression (QR) coefficients within the context of GARMA errors. We propose a modified maximum-likelihood estimation method using an EM algorithm to estimate the target coefficients and derive their statistical properties. The proposed procedure yields estimators that are strongly consistent and asymptotically normal under mild conditions. In order to evaluate the performance of the proposed estimators, a simulation study is conducted employing the minimum bias and Root Mean Square Error (RMSE) criterion. Furthermore, an empirical application is given to demonstrate the effectiveness of the proposed methodology in practice.
Full article
(This article belongs to the Topic Interfacing Statistics, Machine Learning and Data Science from a Probabilistic Modelling Viewpoint)
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Open AccessArticle
Investigating Mechanical Response and Structural Integrity of Tubercle Leading Edge under Static Loads
by
Ali Esmaeili, Hossein Jabbari, Hadis Zehtabzadeh and Majid Zamiri
Modelling 2024, 5(2), 569-584; https://doi.org/10.3390/modelling5020030 - 25 May 2024
Abstract
This investigation into the aerodynamic efficiency and structural integrity of tubercle leading edges, inspired by the agile maneuverability of humpback whales, employs a multifaceted experimental and computational approach. By utilizing static load extensometer testing complemented by computational simulations, this study quantitatively assesses the
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This investigation into the aerodynamic efficiency and structural integrity of tubercle leading edges, inspired by the agile maneuverability of humpback whales, employs a multifaceted experimental and computational approach. By utilizing static load extensometer testing complemented by computational simulations, this study quantitatively assesses the impacts of unique wing geometries on aerodynamic forces and structural behavior. The experimental setup, involving a Wheatstone full-bridge circuit, measures the strain responses of tubercle-configured leading edges under static loads. These measured strains are converted into stress values through Hooke’s law, revealing a consistent linear relationship between the applied loads and induced strains, thereby validating the structural robustness. The experimental results indicate a linear strain increase with load application, demonstrating strain values ranging from 65 με under a load of 584 g to 249 με under a load of 2122 g. These findings confirm the structural integrity of the designs across varying load conditions. Discrepancies noted between the experimental data and simulation outputs, however, underscore the effects of 3D printing imperfections on the structural analysis. Despite these manufacturing challenges, the results endorse the tubercle leading edges’ capacity to enhance aerodynamic performance and structural resilience. This study enriches the understanding of bio-inspired aerodynamic designs and supports their potential in practical fluid mechanics applications, suggesting directions for future research on manufacturing optimizations.
Full article
(This article belongs to the Special Issue Modelling and Simulation of Composite Structures)
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Open AccessArticle
A State-Based Language for Enhanced Video Surveillance Modeling (SEL)
by
Selene Ramirez-Rosales, Luis-Antonio Diaz-Jimenez, Daniel Canton-Enriquez, Jorge-Luis Perez-Ramos, Herlindo Hernandez-Ramirez, Ana-Marcela Herrera-Navarro, Gabriela Xicotencatl-Ramirez and Hugo Jimenez-Hernandez
Modelling 2024, 5(2), 549-568; https://doi.org/10.3390/modelling5020029 - 24 May 2024
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SEL, a State-based Language for Video Surveillance Modeling, is a formal language designed to represent and identify activities in surveillance systems through scenario semantics and the creation of motion primitives structured in programs. Motion primitives represent the temporal evolution of motion evidence. They
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SEL, a State-based Language for Video Surveillance Modeling, is a formal language designed to represent and identify activities in surveillance systems through scenario semantics and the creation of motion primitives structured in programs. Motion primitives represent the temporal evolution of motion evidence. They are the most basic motion structures detected as motion evidence, including operators such as sequence, parallel, and concurrency, which indicate trajectory evolution, simultaneity, and synchronization. SEL is a very expressive language that characterizes interactions by describing the relationships between motion primitives. These interactions determine the scenario’s activity and meaning. An experimental model is constructed to demonstrate the value of SEL, incorporating challenging activities in surveillance systems. This approach assesses the language’s suitability for describing complicated tasks.
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Open AccessArticle
Parameter Choice Strategy That Computes Regularization Parameter before Computing the Regularized Solution
by
Santhosh George, Jidesh Padikkal, Ajil Kunnarath, Ioannis K. Argyros and Samundra Regmi
Modelling 2024, 5(2), 530-548; https://doi.org/10.3390/modelling5020028 - 13 May 2024
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The modeling of many problems of practical interest leads to nonlinear ill-posed equations (for example, the parameter identification problem (see the Numerical section)). In this article, we introduce a new source condition (SC) and a new parameter choice strategy (PCS) for the Tikhonov
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The modeling of many problems of practical interest leads to nonlinear ill-posed equations (for example, the parameter identification problem (see the Numerical section)). In this article, we introduce a new source condition (SC) and a new parameter choice strategy (PCS) for the Tikhonov regularization (TR) method for nonlinear ill-posed problems. The new PCS is introduced using a new SC to compute the regularization parameter (RP) before computing the regularized solution. The theoretical results are verified using a numerical example.
Full article
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Open AccessArticle
Micro-Mechanical Hyperelastic Modelling for (Un)Filled Polyurethane with Considerations of Strain Amplification
by
Saman H. Razavi, Vinicius C. Beber and Bernd Mayer
Modelling 2024, 5(2), 502-529; https://doi.org/10.3390/modelling5020027 - 24 Apr 2024
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Polyurethane (PU) is a very versatile material in engineering applications, whose mechanical properties can be tailored by the introduction of active fillers. The current research aims to (i) investigate the effect of active fillers with varying filler loads on the mechanical properties of
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Polyurethane (PU) is a very versatile material in engineering applications, whose mechanical properties can be tailored by the introduction of active fillers. The current research aims to (i) investigate the effect of active fillers with varying filler loads on the mechanical properties of a PU system and (ii) develop a micro-mechanical model to describe the hyperelastic behavior of (un)filled PU. Three models are taken into consideration: without strain amplification, with constant strain amplification, and with a deformation-dependent strain amplification. The measured uniaxial stress–strain data of the filled PU nanocomposites reveal clear reinforcement due to the incorporation of carbon black at 5, 10 and 20 wt%. In low concentration (1 wt%), for two different grades of carbon black and a fumed silica, it results in a reduction in the mechanical properties. The micro-mechanical model without strain amplification has a good agreement with the measured stress–strain curves at low concentrations of fillers (1 wt%). For higher filled concentrations (5–15 wt%), the micro-mechanical model with constant strain amplification leads to a better prediction performance. For samples with a larger filler volume fraction (20 wt%) and for a commercial adhesive, the model with a deformation-dependent strain amplification effect leads to the best predictions, i.e., highest R2 regarding curve fitting.
Full article
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Open AccessArticle
Numerical Simulation of the Interaction between a Planar Shock Wave and a Cylindrical Bubble
by
Solomon Onwuegbu, Zhiyin Yang and Jianfei Xie
Modelling 2024, 5(2), 483-501; https://doi.org/10.3390/modelling5020026 - 16 Apr 2024
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Three-dimensional (3D) computational fluid dynamics (CFD) simulations have been carried out to investigate the complex interaction of a planar shock wave (Ma = 1.22) with a cylindrical bubble. The unsteady Reynolds-averaged Navier–Stokes (URANS) approach with a level set coupled with volume of fluid
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Three-dimensional (3D) computational fluid dynamics (CFD) simulations have been carried out to investigate the complex interaction of a planar shock wave (Ma = 1.22) with a cylindrical bubble. The unsteady Reynolds-averaged Navier–Stokes (URANS) approach with a level set coupled with volume of fluid (LSVOF) method has been applied in the present study. The predicted velocities of refracted wave, transmitted wave, upstream interface, downstream interface, jet, and vortex filaments are in very good agreement with the experimental data. The predicted non-dimensional bubble and vortex velocities also have great concordance with the experimental data compared with a simple model of shock-induced Rayleigh–Taylor instability (i.e., Richtmyer–Meshkov instability) and other theoretical models. The simulated changes in the bubble shape and size (length and width) against time agree very well with the experimental results. Comprehensive flow analysis has shown the shock–bubble interaction (SBI) process clearly from the onset of bubble compression up to the formation of vortex filaments, especially elucidating the mechanism on the air–jet formation and its development. It is demonstrated for the first time that turbulence is generated at the early phase of the shock cylindrical bubble interaction process, with the maximum turbulence intensity reaching about 20% around the vortex filament regions at the later phase of the interaction process.
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Open AccessArticle
Integrated Modeling of Coastal Processes Driven by an Advanced Mild Slope Wave Model
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Michalis K. Chondros, Anastasios S. Metallinos and Andreas G. Papadimitriou
Modelling 2024, 5(2), 458-482; https://doi.org/10.3390/modelling5020025 - 11 Apr 2024
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Numerical modeling of wave transformation, hydrodynamics, and morphodynamics in coastal regions holds paramount significance for combating coastal erosion by evaluating and optimizing various coastal protection structures. This study aims to present an integration of numerical models to accurately simulate the coastal processes with
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Numerical modeling of wave transformation, hydrodynamics, and morphodynamics in coastal regions holds paramount significance for combating coastal erosion by evaluating and optimizing various coastal protection structures. This study aims to present an integration of numerical models to accurately simulate the coastal processes with the presence of coastal and harbor structures. Specifically, integrated modeling employs an advanced mild slope model as the main driver, which is capable of describing all the wave transformation phenomena, including wave reflection. This model provides radiation stresses as inputs to a hydrodynamic model based on Reynolds-averaged Navier–Stokes equations to simulate nearshore currents. Ultimately, these models feed an additional model that can simulate longshore sediment transport and bed level changes. The models are validated against experimental measurements, including energy dissipation due to bottom friction and wave breaking; combined refraction, diffraction, and breaking over a submerged shoal; wave transformation and wave-generated currents over submerged breakwaters; and wave, currents, and sediment transport fields over a varying bathymetry. The models exhibit satisfactory performance in simulating all considered cases, establishing them as efficient and reliable integrated tools for engineering applications in real coastal areas. Moreover, leveraging the validated models, a numerical investigation is undertaken to assess the effects of wave reflection on a seawall on coastal processes for two ideal beach configurations—one with a steeper slope of 1:10 and another with a milder slope of 1:50. The numerical investigation reveals that the presence of reflected waves, particularly in milder bed slopes, significantly influences sediment transport, emphasizing the importance of employing a wave model that takes into account wave reflection as the primary driver for integrated modeling of coastal processes.
Full article
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Open AccessArticle
Forecasting Future Research Trends in the Construction Engineering and Management Domain Using Machine Learning and Social Network Analysis
by
Gasser G. Ali, Islam H. El-adaway, Muaz O. Ahmed, Radwa Eissa, Mohamad Abdul Nabi, Tamima Elbashbishy and Ramy Khalef
Modelling 2024, 5(2), 438-457; https://doi.org/10.3390/modelling5020024 - 6 Apr 2024
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Construction Engineering and Management (CEM) is a broad domain with publications covering interrelated subdisciplines and considered a key source of knowledge sharing. Previous studies used scientometric methods to assess the current impact of CEM publications; however, there is a need to predict future
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Construction Engineering and Management (CEM) is a broad domain with publications covering interrelated subdisciplines and considered a key source of knowledge sharing. Previous studies used scientometric methods to assess the current impact of CEM publications; however, there is a need to predict future citations of CEM publications to identify the expected high-impact trends in the future and guide new research efforts. To tackle this gap in the literature, the authors conducted a study using Machine Learning (ML) algorithms and Social Network Analysis (SNA) to predict CEM-related citation metrics. Using a dataset of 93,868 publications, the authors trained and tested two machine learning classification algorithms: Random Forest and XGBoost. Validation of the RF and XGBoost resulted in a balanced accuracy of 79.1% and 79.5%, respectively. Accordingly, XGBoost was selected. Testing of the XGBoost model revealed a balanced accuracy of 80.71%. Using SNA, it was found that while the top CEM subdisciplines in terms of the number of predicted impactful papers are “Project planning and design”, “Organizational issues”, and “Information technologies, robotics, and automation”; the lowest was “Legal and contractual issues”. This paper contributes to the body of knowledge by studying the citation level, strength, and interconnectivity between CEM subdisciplines as well as identifying areas more likely to result in highly cited publications.
Full article
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Open AccessArticle
Numerical Analysis of Crack Propagation in an Aluminum Alloy under Random Load Spectra
by
Fangli Wang, Jie Zheng, Kai Liu, Mingbo Tong and Jinyu Zhou
Modelling 2024, 5(2), 424-437; https://doi.org/10.3390/modelling5020023 - 4 Apr 2024
Abstract
This study develops a rapid algorithm coupled with the finite element method to predict the fatigue crack propagation process and select the enhancement factor for the equivalent random load spectrum of accelerated fatigue tests. The proposed algorithm is validated by several fatigue tests
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This study develops a rapid algorithm coupled with the finite element method to predict the fatigue crack propagation process and select the enhancement factor for the equivalent random load spectrum of accelerated fatigue tests. The proposed algorithm is validated by several fatigue tests of an aluminum alloy under the accelerated random load spectra. In the validation process, two kinds of panels with different geometries and sizes are used to calculate the stress intensity factor, critical crack length, and crack propagation life. The simulated and experimental findings indicate that when the aluminum alloy is in a low plasticity state, the crack propagation life exhibits a linear relationship with the acceleration factor. When the aluminum alloy is in a high plasticity state, this study proposes an empirical formula to calculate the equivalent stress intensity factor and crack propagation life. The normalized empirical formula is independent of the geometry and size of different samples, although the fracture processes are different in the two kinds of panels used in our study. Overall, the numerical method proposed in this paper can be applied to predict the fatigue crack propagation life for the random spectrum of large samples based on the results of the simulated accelerated crack propagation process and the accelerated fatigue tests of small samples to reduce the cost and time of the testing.
Full article
(This article belongs to the Special Issue Feature Papers of Computational Modelling and Simulation for Fatigue and Fracture of Engineering Materials and Structures)
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Open AccessArticle
On Mechanical and Chaotic Problem Modeling and Numerical Simulation Using Electric Networks
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Pedro Aráez, José Antonio Jiménez-Valera and Iván Alhama
Modelling 2024, 5(2), 410-423; https://doi.org/10.3390/modelling5020022 - 25 Mar 2024
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After reviewing the use of electrical circuit elements to model dynamic processes or the operation of devices or equipment, both in real laboratory implementations and through ideal circuits implemented in simulation software, a network model design protocol is proposed. This approach, following the
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After reviewing the use of electrical circuit elements to model dynamic processes or the operation of devices or equipment, both in real laboratory implementations and through ideal circuits implemented in simulation software, a network model design protocol is proposed. This approach, following the basic rules of circuit theory, makes use of controlled generators to implement any type of nonlinearity contained in the governing equations. Such a protocol constitutes an interesting educational tool that makes it possible for nonexpert students in mathematics to design and numerically simulate complex physical processes. Three applications to mechanical and chaotic problems are presented to illustrate the versatility of the proposed protocol.
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Open AccessArticle
Computational Modelling of Intra-Module Connections and Their Influence on the Robustness of a Steel Corner-Supported Volumetric Module
by
Si Hwa Heng, David Hyland, Michael Hough and Daniel McCrum
Modelling 2024, 5(1), 392-409; https://doi.org/10.3390/modelling5010021 - 21 Mar 2024
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This paper investigates the robustness of a single 3D volumetric corner-supported module made of square hollow-section (SHS) columns. Typically, the moment–rotation (M-θ) behaviour of connections within the module (intra-module) is assumed to be fully rigid rather than semi-rigid, resulting in inaccurate assessment (i.e.,
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This paper investigates the robustness of a single 3D volumetric corner-supported module made of square hollow-section (SHS) columns. Typically, the moment–rotation (M-θ) behaviour of connections within the module (intra-module) is assumed to be fully rigid rather than semi-rigid, resulting in inaccurate assessment (i.e., overestimated vertical stiffness) during extreme loading events, such as progressive collapse. The intra-module connections are not capable of rigidly transferring the moment from the beams to the SHS columns. In this paper, a computationally intensive shell element model (SEM) of the module frame is created. The M-θ relationship of the intra-module connections in the SEM is firstly validated against test results by others and then replicated in a new simplified phenomenological beam element model (BEM), using nonlinear spring elements to capture the M-θ relationship. Comparing the structural behaviour of the SEM and BEM, under notional support removal, shows that the proposed BEM with semi-rigid connections (SR-BEM) agrees well with the validated SEM and requires substantially lower modelling time (98.7% lower) and computational effort (97.4% less RAM). When compared to a BEM with the typically modelled fully rigid intra-module connections (FR-BEM), the vertical displacement in the SR-BEM is at least 16% higher. The results demonstrate the importance of an accurate assessment of framing rotational stiffness and the benefits of a computationally efficient model.
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Open AccessArticle
A CALPHAD-Informed Enthalpy Method for Multicomponent Alloy Systems with Phase Transitions
by
Robert Scherr, Philipp Liepold, Matthias Markl and Carolin Körner
Modelling 2024, 5(1), 367-391; https://doi.org/10.3390/modelling5010020 - 8 Mar 2024
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Solid–liquid phase transitions of metals and alloys play an important role in many technical processes. Therefore, corresponding numerical process simulations need adequate models. The enthalpy method is the current state-of-the-art approach for this task. However, this method has some limitations regarding multicomponent alloys
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Solid–liquid phase transitions of metals and alloys play an important role in many technical processes. Therefore, corresponding numerical process simulations need adequate models. The enthalpy method is the current state-of-the-art approach for this task. However, this method has some limitations regarding multicomponent alloys as it does not consider the enthalpy of mixing, for example. In this work, we present a novel CALPHAD-informed version of the enthalpy method that removes these drawbacks. In addition, special attention is given to the handling of polymorphic as well as solid–liquid phase transitions. Efficient and robust algorithms for the conversion between enthalpy and temperature were developed. We demonstrate the capabilities of the presented method using two different implementations: a lattice Boltzmann and a finite difference solver. We proof the correct behaviour of the developed method by different validation scenarios. Finally, the model is applied to electron beam powder bed fusion—a modern additive manufacturing process for metals and alloys that allows for different powder mixtures to be alloyed in situ to produce complex engineering parts. We reveal that the enthalpy of mixing has a significant effect on the temperature and lifetime of the melt pool and thus on the part properties.
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Open AccessArticle
Effects of Chemical Short-Range Order and Temperature on Basic Structure Parameters and Stacking Fault Energies in Multi-Principal Element Alloys
by
Subah Mubassira, Wu-Rong Jian and Shuozhi Xu
Modelling 2024, 5(1), 352-366; https://doi.org/10.3390/modelling5010019 - 28 Feb 2024
Cited by 1
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In the realm of advanced material science, multi-principal element alloys (MPEAs) have emerged as a focal point due to their exceptional mechanical properties and adaptability for high-performance applications. This study embarks on an extensive investigation of four MPEAs—CoCrNi, MoNbTa, HfNbTaTiZr, and HfMoNbTaTi—alongside key
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In the realm of advanced material science, multi-principal element alloys (MPEAs) have emerged as a focal point due to their exceptional mechanical properties and adaptability for high-performance applications. This study embarks on an extensive investigation of four MPEAs—CoCrNi, MoNbTa, HfNbTaTiZr, and HfMoNbTaTi—alongside key pure metals (Mo, Nb, Ta, Ni) to unveil their structural and mechanical characteristics. Utilizing a blend of molecular statics and hybrid molecular dynamics/Monte Carlo simulations, the research delves into the impact of chemical short-range order (CSRO) and thermal effects on the fundamental structural parameters and stacking fault energies in these alloys. The study systematically analyzes quantities such as lattice parameters, elastic constants ( , , and ), and generalized stacking fault energies (GSFEs) across two distinct structures: random and CSRO. These properties are then evaluated at diverse temperatures (0, 300, 600, 900, 1200 K), offering a comprehensive understanding of temperature’s influence on material behavior. For CSRO, CoCrNi was annealed at 350 K and MoNbTa at 300 K, while both HfMoNbTaTi and HfNbTaTiZr were annealed at 300 K, 600 K, and 900 K, respectively. The results indicate that the lattice parameter increases with temperature, reflecting typical thermal expansion behavior. In contrast, both elastic constants and GSFE decrease with rising temperature, suggesting a reduction in resistance to stability and dislocation motion as thermal agitation intensifies. Notably, MPEAs with CSRO structures exhibit higher stiffness and GSFEs compared to their randomly structured counterparts, demonstrating the significant role of atomic ordering in enhancing material strength.
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Open AccessArticle
Modeling and Simulation of a Planar Permanent Magnet On-Chip Power Inductor
by
Jaber A. Abu Qahouq and Mohammad K. Al-Smadi
Modelling 2024, 5(1), 339-351; https://doi.org/10.3390/modelling5010018 - 22 Feb 2024
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The on-chip integration of a power inductor together with other power converter components of small sizes and high-saturation currents, while maintaining a desired or high inductance value, is here pursued. The use of soft magnetic cores increases inductance density but results in a
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The on-chip integration of a power inductor together with other power converter components of small sizes and high-saturation currents, while maintaining a desired or high inductance value, is here pursued. The use of soft magnetic cores increases inductance density but results in a reduced saturation current. This article presents a 3D physical model and a magnetic circuit model for an integrated on-chip power inductor (OPI) to double the saturation current using permanent magnet (PM) material. A ~50 nH, 7.5 A spiral permanent magnet on-chip power inductor (PMOI) is here designed, and a 3D physical model is then developed and simulated using the ANSYS®/Maxwell® software package (version 2017.1). The 3D physical model simulation results agree with the presented magnetic circuit model, and show that in the example PMOI design, the addition of the PM increases the saturation current of the OPI from 4 A to 7.5 A, while the size and inductance value remain unchanged.
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